斯坦福《算法：设计与分析(I)》课程(2018) by Tim Roughgarden
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https://www.youtube.com/playlist?list=PLXFMmlk03Dt7Q0xr1PIAriY5623cKiH7V
Algorithms: Design and Analysis (Part I) by Tim Roughgarden
Slides:http://timroughgarden.org/mooc/algo1slides.zip
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1 1 Why Study Algorithms 4 min
04:16
1 2 Integer Multiplication 9 min
08:39
1 3 Karatsuba Multiplication 13 min
12:40
1 4 About the Course 17 min
17:20
1 5 Merge Sort Motivation and Example 9 min
08:45
1 6 Merge Sort Pseudocode 13 min
12:52
1 7 Merge Sort Analysis 9 min
09:03
1 8 Guiding Principles for Analysis of Algorithms 15 min
15:17
2 1 The Gist 14 min
14:13
2 2 Big Oh Notation 4 min
04:10
2 3 Basic Examples 7 min
07:28
2 4 Big Omega and Theta 7 min
07:32
2 5 Additional Examples Review Optional 8 min
07:52
3 1 On log n Algorithm for Counting Inversions I 13 min
12:36
3 2 On log n Algorithm for Counting Inversions II 17 min
16:34
3 3 Strassen 's Subcubic Matrix Multiplication Algorithm 22 min
22:33
3 4 On log n Algorithm for Closest Pair I Advanced Optional 32 min
31:47
3 5 On log n Algorithm for Closest Pair II Advanced Optional 19 min
19:00
4 1 Motivation 8 min
07:48
4 2 Formal Statement 10 min
09:59
4 3 Examples 13 min
13:06
4 4 Proof I 10 min
09:58
4 5 Interpretation of the 3 Cases 11 min
10:47
4 6 Proof II 16 min
16:17
5 1 Quicksort Overview 12 min
12:10
5 2 Partitioning Around a Pivot 25 min
24:56
5 3 Correctness of Quicksort Review Optional 11 min
10:40
5 4 Choosing a Good Pivot 22min
22:26
6 1 Analysis I A Decomposition Principle Advanced Optional 22 min
21:49
6 2 Analysis II The Key Insight Advanced Optional 12min
11:48
6 3 Analysis III Final Calculations Advanced Optional 9min
08:58
7 1 Part I Review Optional 25 min
25:58
7 2 Part II Review Optional 17 min
17:22
8 1 Randomized Selection Algorithm 22 min
21:41
8 2 Randomized Selection Analysis 21 min
20:35
8 3 Deterministic Selection Algorithm Advanced Optional 17 min
16:57
8 4 Deterministic Selection Analysis I Advanced Optional 22 min
22:03
8 5 Deterministic Selection Analysis II Advanced Optional 13 min
12:43
8 6 Omegan log n Lower Bound for Comparison Based Sorting Advanced Optiona
13:31
9 1 Graphs and Minimum Cuts 16 min
15:51
9 2 Graph Representations 14 min
14:23
9 3 Random Contraction Algorithm 9 min
08:45
9 4 Analysis of Contraction Algorithm 30 min
30:05
9 5 Counting Minimum Cuts 7 min
07:19
10 1 Graph Search Overview 23 min
23:21
10 2 Breadth First Search BFS The Basics 14 min
14:13
10 3 BFS and Shortest Paths 8 min
07:45
10 4 BFS and Undirected Connectivity 13 min
13:19
10 5 Depth First Search DFS The Basics 7 min
07:25
10 6 Topological Sort 22 min
21:54
10 7 Computing Strong Components The Algorithm 29 min
29:22
10 8 Computing Strong Components The Analysis 26 min
26:04
10 9 Structure of the Web Optional 19 min
18:51
11 1 Dijkstra 's Shortest Path Algorithm 21 min
20:46
11 2 Dijkstra 's Algorithm Examples 13 min
12:46
11 3 Correctness of Dijkstra 's Algorithm Advanced Optional 19 min
19:18
11 4 Dijkstra 's Algorithm Implementation and Running Time 26 min
26:29
12 1 Data Structures Overview 5 min
04:37
12 2 Heaps Operations and Applications 18 min
18:12
12 3 Heaps Implementation Details Advanced Optional 21 min
20:59
13 1 Balanced Search Trees Operations and Applications 11 min
10:56
13 2 Binary Search Tree Basics, Part I 13 min
13:08
13 3 Binary Search Tree Basics, Part II 30 min
30:10
13 4 Red Black Trees 21 min
21:19
13 5 Rotations Advanced Optional 8 min
07:37
13 6 Insertion in a Red Black Tree Advanced 15 min
14:42
14 1 Hash Tables Operations and Applications 19 min
19:22
14 2 Hash Tables Implementation Details, Part I 19 min
18:59
14 3 Hash Tables Implementation Details, Part II 22 min
22:14
15 1 Pathological Data Sets and Universal Hashing Motivation 22 min
21:55
15 2 Universal Hashing Definition and Example Advanced Optional 26 min
25:45
15 3 Universal Hashing Analysis of Chaining Advanced Optional 19 min
18:41
15 4 Hash Table Performance with Open Addressing Advanced Optional 16 min
15:46
16 1 Bloom Filters The Basics 16 min
15:23
16 2 Bloom Filters Heuristic Analysis 13 min
13:27
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